Convolutional Autoencoders, Clustering and POD for Low-dimensional Parametrization of Navier-Stokes Equations.
Yongho KimJan HeilandPublished in: CoRR (2023)
Keyphrases
- low dimensional
- high dimensional data
- data points
- clustering algorithm
- high dimensional
- k means
- navier stokes equations
- multidimensional scaling
- dimensionality reduction
- denoising
- clustering method
- high dimensional data space
- euclidean space
- restricted boltzmann machine
- cluster analysis
- data clustering
- manifold learning
- hierarchical clustering
- pattern recognition
- input space
- spectral clustering
- data objects
- self organizing maps
- unsupervised learning
- vector space
- information theoretic
- deep learning
- outlier detection